Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 311 545 406 877 466 625 463 556 255 94 790 431 432 265 266 512 586 376 464 87
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 311 877 94 586 556 545 790 NA 512 NA 406 466 376 463 625 NA 432 265 87 464 431 255 266
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 3 2 5 1 3 5 2 3 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "r" "x" "n" "y" "j" "Z" "K" "C" "B" "N"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
integer(0)
which( manyNumbersWithNA > 900 )
integer(0)
which( is.na( manyNumbersWithNA ) )
[1] 8 10 16
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
integer(0)
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
integer(0)
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
integer(0)
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "Z" "K" "C" "B" "N"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "r" "x" "n" "y" "j"
manyNumbers %in% 300:600
[1] TRUE TRUE TRUE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE TRUE TRUE TRUE TRUE FALSE
which( manyNumbers %in% 300:600 )
[1] 1 2 3 5 7 8 12 13 16 17 18 19
sum( manyNumbers %in% 300:600 )
[1] 12
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" "small" "large" "large" "large" "large" NA "large" NA "small" "small" "small" "small" "large" NA
[17] "small" "small" "small" "small" "small" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "small" "large" "large" "large" "large" "UNKNOWN" "large" "UNKNOWN" "small" "small" "small"
[14] "small" "large" "UNKNOWN" "small" "small" "small" "small" "small" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 877 0 586 556 545 790 NA 512 NA 0 0 0 0 625 NA 0 0 0 0 0 0 0
unique( duplicatedNumbers )
[1] 5 3 2 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 3 2 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 2
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 877
which.min( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 87
range( manyNumbersWithNA, na.rm = TRUE )
[1] 87 877
manyNumbersWithNA
[1] 311 877 94 586 556 545 790 NA 512 NA 406 466 376 463 625 NA 432 265 87 464 431 255 266
sort( manyNumbersWithNA )
[1] 87 94 255 265 266 311 376 406 431 432 463 464 466 512 545 556 586 625 790 877
sort( manyNumbersWithNA, na.last = TRUE )
[1] 87 94 255 265 266 311 376 406 431 432 463 464 466 512 545 556 586 625 790 877 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 877 790 625 586 556 545 512 466 464 463 432 431 406 376 311 266 265 255 94 87 NA NA NA
manyNumbersWithNA[1:5]
[1] 311 877 94 586 556
order( manyNumbersWithNA[1:5] )
[1] 3 1 5 4 2
rank( manyNumbersWithNA[1:5] )
[1] 2 5 1 4 3
sort( mixedLetters )
[1] "B" "C" "j" "K" "n" "N" "r" "x" "y" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 7.0 9.0 1.5 1.5 7.0 3.5 3.5 5.0 10.0 7.0
rank( manyDuplicates, ties.method = "min" )
[1] 6 9 1 1 6 3 3 5 10 6
rank( manyDuplicates, ties.method = "random" )
[1] 6 9 1 2 7 4 3 5 10 8
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 1.49291587 0.11585602 -0.60420434 -0.02423643 0.78162146
[11] 0.56812871 -0.17714063 1.08703783 0.34082446 0.19130916
round( v, 0 )
[1] -1 0 0 0 1 1 0 -1 0 1 1 0 1 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 1.5 0.1 -0.6 0.0 0.8 0.6 -0.2 1.1 0.3 0.2
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 1.49 0.12 -0.60 -0.02 0.78 0.57 -0.18 1.09 0.34 0.19
floor( v )
[1] -1 -1 0 0 1 1 0 -1 -1 0 0 -1 1 0 0
ceiling( v )
[1] -1 0 0 1 1 2 1 0 0 1 1 0 2 1 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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